Slashing operational-costs-via-driveless-ran-optimization

White Paper

Slashing Operational Costs via Driveless RAN Optimization 1

Executive Summary

As mobile networks grow in size and complexity, efficient management of daily network

operations become one of the most crucial tasks of mobile network operators(MNOs). In this

white paper, we discuss how 3GPP defined Minimization of Drive Tests (MDT) data can be

utilized in lieu of drive testing to realize driveless Radio Access Network (RAN) optimization.

The approach outlined here does not require GNSS (Global Navigation Satellite System)

location information from mobile terminals or applications. Field results obtained by North

American Tier-1 mobile operators have shown that more than 50% reduction in operational

expenses is possible from drive test elimination when introducing new sites/clusters.

Introduction to MDT

LTE continues to grow faster than any other mobile communications system technology in

history since its introduction in December of 2009. As of January 2016, 480 operators have

commercially launched LTE systems, reaching to 13% of mobile connections worldwide.

Similar to 3G, LTE deployments introduce significant operational and capital expenditures for

mobile operators. Traditionally, test terminals are used to measure signal and service quality

levels (e.g. RSRP, RSRQ, SINR, throughput, access fails and drops) during LTE deployments.

Drive test logs are collected and analyzed to rectify any issues encountered. This is a very

tedious process where large log files need to be handled and analyzed with post processing

tools to come up with conclusions. In practice, the whole drive testing process has to be

repeated several times due to equipment misconfigurations, failures noticed from earlier tests

and important routes which were not driven previously. Also, after each time RF related

optimization changes are applied (e.g. electrical antenna tilt changes), drive testing analysis is

typically re-run to assess the new results from the field.

3GPP, a global partnership that defines the rules of todays mobile communications systems,

specified the standards of how LTE networks should produce data to minimize traditional drive

testing efforts under the Minimization of Drive Tests (MDT) initiative.

In this white paper, we discuss how 3GPP defined MDT data can be used to implement a

driveless RAN optimization framework for mobile operators to dramatically reduce their

operational expenses.

Slashing Operational Costs via Driveless RAN Optimization 2

Shortcomings of Drive Testing

Since the 1990s, mobile subscribers have experienced a dramatic increase in network

capacity, starting with 9.6 Kbps CS download rates in GSM to more than 300 Mbps with LTE-

A. However, RAN optimization processes to `tune` mobile networks have not changed much

within this period to keep up with the advancements.

In a typical LTE network deployment scenario, the first step is to design the network while

taking into account the expected subscriber base, service quality committed to end users, and

the RAN budgets, the most expensive part of CapEx. Then, eNBs are deployed as designed

and budgeted typically with lower density over an existing 2G/3G radio network layer. At this

`pre-launch` phase, drive tests are performed to simulate subscriber behavior and to identify

any immediate issues with the deployment. Following the commercial launch of planned sites,

more eNBs are gradually added to enhance both the coverage and the capacity of the network

while introducing minimum disturbance for commercial users. Unless the parameters are

properly tuned, new site additions can potentially disturb existing neighborhood sites. Because

of the need to test the footprint of each added sites coverage, drive testing becomes an

important task in this phase.

Shortcomings of drive testing during this `post-launch` phase are as follows:

Long testing duration required: Assuming an urban region with average site-to-site distance of

1-3 miles where 200 eNBs are on-aired, every new eNB added to the region after cluster

launch requires an average of 10-15 miles of drive testing (excluding drives to get/return to the

site). This corresponds to 1,000 1,500 miles of driving if 100 eNBs are added. This

significantly increases the time it takes the MNOs to realize revenues from the new assets

added.

High volumes of data to process: If we consider that Tier-1 operators have thousands of eNBs,

the amount of drive test data that is required to be collected and analyzed amounts to huge

volumes. For a 25-eNB urban cluster in a 3 miles x 1 miles area with 4 pieces of test equipment

including a scanner searching three separate bands, the amount of drive data can exceed 1

GB of raw files for a 7-hour drive.

Sampling limitation: It may take a large number of tests to be repeated in order to replicate a

specific drop or a block problem. More tests mean more logs and consequently result in wasted

resources.

Slashing Operational Costs via Driveless RAN Optimization 3

Indoor user experience: Drive testing is performed in outdoor environments. However, the

majority of subscriber traffic takes place indoors. Thus, conventional drive testing approach

cannot verify and improve indoor subscriber experience.

MDT as a Driveless Solution for Post-Launch Optimization

As a response to the shortcomings of drive testing, 3GPP published Minimization of Drive

Tests (MDT) specifications [1, 2, and 3] to provide a more efficient approach to optimization.

Using the measurements taken from MDT-supported equipment, operators can select and

display all or a portion of the UEs (User Equipment) under specified eNBs covering a particular

geographical region or specific IMSIs, IMEIs or IMEI-TACs [4] across the network. These

standardized UE and equipment measurements are then used for various needs including new

site/cluster RF Tuning or VIP customer complaint handling. The output measurements of MDT

are also normalized to be used as inputs to SON (Self Organizing Networks) use cases and

algorithms such as CCO (Coverage and Capacity Optimization) [5, 6].

Driveless MDT optimization complements the mobile operator`s `post-launch` deployment

process as follows:

Step 1. Site installation and eNB integration to OSS

Step 2. Identification and resolution of hardware issues (e.g. PIM, RSSI, VSWR)

Step 3. eNB and MME configuration audits (e.g. golden parameters, TAC, PCI, RSI)

Step 4. Pre-launch single site audit (e.g. crossed feeder/MIMO verification,

stationary DL/UL throughput check, testing of Tx imbalance issues, co-site handover

check)

Step 5. eNB and cluster launch

Step 6. Post-launch optimization with driveless MDT data

Once an eNB or cluster is launched for commercial traffic, driveless RAN optimization process

starts. MDT configuration is done by specifying eNB/E-UTRAN cell list, time, duration of

measurement, messages, events to be collected over Uu and eNB external interfaces and

sampling rate of calls (e.g. 50%). Typically, files are created per 15-minute intervals on eNBs

and then forwarded to OSS (Logged MDT). Streaming transfer option directly to an external

server is also defined in the standards (Immediate MDT).

Slashing Operational Costs via Driveless RAN Optimization 4

KPI results are calculated and analyzed per geographic bin where resolution depends on

operator requirements (e.g. ranging from 50m x 50m to 500m x 500m).

Various Key Performance Indicators (i.e. KPIs1) ranging from availability, accessibility,

retainability, mobility, integrity and throughput for different services (e.g. PS Data, VoLTE,

CSFB) should be above target performance thresholds set by the mobile operator for best

subscriber experience.

An important benefit of the driveless approach is that, the operator can improve service quality

experienced by subscribers in every part of the network per geographic bin. Driveless post-

launch optimization improves bad subscriber experience even for cells with very good network

KPIs, which reflect the accumulated results of all subscribers in a cell.

Additionally, geographic bin analysis facilitates policy tuning per bin, where important KPIs

(e.g. throughput and coverage) are weighted with larger coefficients than others during the

calculation of a unified quality index per bin.

Figure 1 - Cost calculation example for a geographic bin

1 3GPP initial output to extend traditional KPI definition to Service Experience KQI is described under

TR 32.862. [7,8]

Slashing Operational Costs via Driveless RAN Optimization 5

The following Figure 2 - Drive Testing vs. Driveless Tuning of a newly added site/cluster to

commercial network compares Drive Testing with driveless MDT based network tuning to

emphasize the shortened duration and minimized effort of the driveless solution.

Figure 2 - Driv